Are You Ready to Start Using Data Analytics to Improve Your Bottom Line?

By jenny

September 08, 2018

Read Time: 10 minutes

So, you and your team have decided to go all in on data analytics. You’ve started collecting data, and you were able to get Google Data Studio up and running. Now you have a plethora of pie charts, time series, and tables. They look fantastic and everyone exchanges high fives. Analytics is about to change your company. But then...nothing happens. A few months go by, and your beautiful dashboards are collecting dust. You’re not sure how the dashboards are supposed to make your business more effective. You think to yourself, “Google Data Studio sucks!” The reality is, though, a platform by itself won’t instantly allow you to achieve all your goals. But what are you missing?

If we tried to answer that question for everyone at the same time this would be a much longer article. Instead, we’re going to review some key questions you need to ask your internal team before you begin the process of looking for a Business Intelligence (BI) platform. Then, we’ll dive into the pros and cons of the three most popular BI platforms on the market, while recognizing that there’s not necessarily going to be an easy, one-size-fits-all solution. We’ll start with Google Data Studio (which isn’t actually so bad, of course) and we’ll work our way up to a more comprehensive Power BI platform, which is what our team often uses.

One last thing: we’ll be using the term “Business Intelligence platform” as something of a catchall, with the intention of looking at three rather different products. At the end of the day, Business Intelligence is a bit of a nebulous term (in fact, at Anvil, we changed the name of our Business Intelligence team to the Decision Science team, because we felt like that name was more descriptive). Business Intelligence is all about leveraging data to make smarter decisions. A platform can help you accomplish that, but it’s not a magic wand. In data collection, we talk about “garbage in, garbage out,” meaning if your data collection isn’t set up properly, the data you collect won’t be useful. In the same way, you can collect all the pristine, useful data in the world, but you still have to put that data to use. That’s where Business Intelligence platforms come in. Ultimately though, it will be up to you and your team, with help from a BI platform (or several), to turn your data into actionable insights.

A key decision your team must first make is gaining alignment on the key performance indicators you’ll want to track with the BI platform. (Hopefully, you identified objectives and KPIs before you even started collecting data—for more on this, see our Google Analytics whitepaper). So, before we get down to the nitty-gritty of comparing BI platforms, here are some key questions you need to take into account:

Is the BI platform going to be used to drive insight into marketing initiatives, or broader operational and financial data?

What data sources will you need it to connect to?

Will you primarily be using it to generate reports or dig into the data for actionable insights that can change your strategy (such as: what is the lifetime value of customers that first buy product X from us versus product Y)?

All of the above, or something totally different?

Some other important questions to consider:

Who will be using the platform (and how tech savvy are they)?

How intuitive or user-friendly will the interface need to be?

What’s your budget?

Is investing in a more expensive platform (potentially starting in the range of $10,000 per year, depending on your needs and the size of your company) an option for you? If so, is it the right option?

If you pay for a more expensive platform, are you confident you’ll be able to leverage that platform to make a return on your investment?

Okay, now let’s take a look at a few of the different BI platforms out there.

Google Data Studio

It was actually our Decision Science team that recommended the title for this post. They were kidding...mostly.

Google Data Studio is great for those just getting started with BI and looking to get their feet wet in reporting and analytics. If you’re reading this, chances are you might have already played around a little with Google Data Studio.

Pros:

Free! No initial investment means Data Studio is perfect for those who just want to test the waters.

Easy to use: Intuitive, drag-and-drop functionality means it won’t take you long to get up and running with this platform. Plus, it’s 100% web-based, so there aren’t specific OS requirements.

Robust connections to Google Analytics and AdWords: Because it’s built by Google, it syncs easily and performs well with other Google products.

Cons:

Limited visualizations: Unlike more advanced platforms, Data Studio doesn’t provide for much customization when it comes to creating visuals with your data.

Siloed data: Even with “blended” reporting, data cannot easily be joined. Also, data transformation is limited to only a few options.

Lack of advanced security: If data security is a high priority, this might not be the best choice for you.

Conclusion: Data Studio is an excellent (and free) way to get started organizing and visualizing your data from Google Analytics and certain other channels, but it lacks connections to some important data sources, like Facebook, and it doesn’t offer many customization options. Depending on your needs and your resources, you might want to consider something more comprehensive down the road.

Excel — Power Query and Power Pivot

Here’s a joke from our Decision Science team: “The third most popular feature in software development is “Export to Excel.” Number one and number two are “OK” and “Cancel.”

Hilarious, right? Here’s the thing: tons of people use Excel but many aren’t aware of the full range of its BI capabilities.

After getting started with Google Data Studio and getting a feel for how BI and data analysis might be able to help you in your digital marketing efforts, or whatever job you’re attempting to accomplish, you might find yourself wanting to try out a more powerful platform, one that will allow you to connect to a wider variety of data channels, blend your data to better identify patterns and trends, and create more customized visualizations.

The good news is you might be able to accomplish all these things using a platform that is probably already sitting on your desktop: Excel. As long as you’re running it on a PC and not a Mac, you can leverage the free, built-in features Power Query and Power Pivot to transform Excel into a robust BI platform.

Pros:

Widely used: Contrary to the opinion of some, Excel is nowhere close to dying. In fact, it’s more relevant now than it has been in many years.

Multi-platform: With the popularity of Power Query, Excel is now a multi-platform ETL solution and offers seamless integration with other Microsoft products, such as Power BI.

Functionality: If you’re willing to invest the time to learn it, Excel has the capability to do an enormous range of data processing to help you achieve your BI goals.

Cons:

Complexity: Microsoft estimates that 95% of Excel users only take advantage of 5% of the program’s capabilities.

Compatibility: To fully leverage Excel as a BI platform, you can’t run it on a Mac.

Accessibility: Excel is not designed to be “plug and play.” It will take time and effort to fully realize Excel’s potential as a BI platform.

Conclusion: Excel offers a ton of capabilities, particularly if you’re running Power Query or Power Pivot on Windows. However, while Excel provides a wider range of functionality, it isn’t as intuitive or user-friendly as Google Data Studio.

Power BI

If you’re serious about Business Intelligence, and you’ve determined that you need a platform that can combine custom visualizations, integrated data connectors, and complex programming capabilities, you might be ready to consider a premium BI platform such as Microsoft’s Power BI.

Pros:

Integration: As a Microsoft product, Power BI can be integrated with the Microsoft Office Suite and the Microsoft stack.

Programming: It allows for the use of programming languages like R, Python, and others.

High-level capabilities: It offers custom visualizations and allows for the utilization of Natural Language Querying, machine learning, and mobile functionality.

Cons:

Pricing: The premium pricing options can be difficult to understand.

Compatibility: Desktop development is not available for Macs.

Transitioning: To fully take advantage of a high-powered, system-wide BI platform, it will take time and training to transition users into a “Self-service” approach (as opposed to the more traditional, “Send to me” approach, where a report, for example, would need to be sent, instead of simply accessed via “Self-service”).

Conclusion: Power BI offers an impressive array of customization, visualization, and functionality. However, if you don’t have at least one member of your team (and/or a partner like Anvil) devoted to implementing and managing BI, it might be hard to draw value from this platform or other high-powered, premium BI platforms.

The takeaway:

The hard truth is that implementing BI is a difficult process. Somewhere between 70 and 80 percent of businesses fail when they try to implement BI initiatives.* Some implementations are unsuccessful because companies try to use the wrong platform, but implementations are just as likely to fail because they lack company-wide buy-in, or because companies attempt to implement too quickly, forgetting to take a “crawl-walk-run” approach.

All that said, there is a reason why there’s so much buzz around BI. As difficult as it can be to implement, the potential of BI to help any company is immense. Remember, at its core, BI means leveraging data to make better decisions—ensuring your company is guided by hard data instead of guesswork.

The key to making BI work for your company isn’t just about choosing the right platform. It’s even more important to find the right people who can leverage your data in the right ways. Whether you’re just getting started, learning to walk, or ready to run when it comes to BI, working with the right team is crucial. This could mean investing in an in-house data team or partnering with an agency.

At Anvil, our Decision Science team has experience with every aspect of Business Intelligence, from developing customized dashboards and creating advanced visualizations to identifying inefficiencies in marketing strategy. If you are seeking help with Business Intelligence, Decision Science, or turning your company’s data into actionable insights, get in touch.

Jenny Bristow is the CEO and Co-Founder of Anvil, a digital + analytics agency in St. Louis, Missouri. Anvil focuses on creating data-driven digital strategies that help clients develop scalable, measurable digital marketing programs for clients in the healthcare, education and manufacturing space. Prior to starting Anvil, Jenny launched, grew and sold a digital agency in Seattle, Washington and worked at Amazon.com. She was named one of St. Louis Business Journal’s 30 under 30, won a Stevie Award for Female Entrepreneur of the Year in 2018 and speaks regularly at industry and local events.